Book Image

Scientific Computing with Python - Second Edition

By : Claus Führer, Jan Erik Solem, Olivier Verdier
Book Image

Scientific Computing with Python - Second Edition

By: Claus Führer, Jan Erik Solem, Olivier Verdier

Overview of this book

Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing.
Table of Contents (23 chapters)
20
About Packt
22
References

9.3 Iterable objects

A for loop is primarily used to traverse a list, but it picks the elements of the list one at a time. In particular, there is no need to store the whole list in memory for the loop to work properly. The mechanism that allows for loops to work without lists is that of iterators.

An iterable object produces objects to be passed to a loop. Such an object may be used inside a loop as if it were a list:

for element in obj:
    ...

The notion of iterable objects thus generalizes the idea of lists.

The simplest example of an iterable object is given by lists. The produced objects are simply the objects stored in the list:

L = ['A', 'B', 'C']
for element in L:
    print(element)

An iterable object need not produce existing objects. The objects may, instead, be produced on the fly.

A typical iterable is the object returned by the function range. This function works as if it would generate...